Fault Detection of Rotating Machinery From Bicoherence Analysis of Vibration Data

Halim, Enayet B.; Choudhury, M.A.A. Shoukat; Shah, Sirish L.; Zuo, Ming J.

doi:10.3182/20060829-4-cn-2909.00225

Cited by 4 publications

(3 citation statements)

References 4 publications

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“…This method is ideal for non-linear and non-Gaussian signal analysis along with its ability to identify correlation or phase coupling in time series. Whereas, the 2 nd order Fourier transformation of a time domain's 3 rd order cumulants is identified as bispectrum, which can be found using the following equation [19,20]:…”

Section: Signal Processing Methodsmentioning

confidence: 99%

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Frequency Coupling Analysis in Spark Ignition Engine Using Bispectral Method and Ensemble Empirical Mode Decomposition

Yacoubi¹,

Samuel²

2022

SAE Technical Paper Series

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Internal combustion (IC) engines are the current dominant power source used in the automotive industry for hybrid vehicles. The combustion process of IC engines involves various parameters, which are linked to the overall performance of the driveline. Therefore, finding the frequency coupling between the manifold pressure, incylinder pressure and output crankshaft speed will provide an insight into the reasons for torque fluctuations and its effect on driveline performance. The present work introduces a methodology to analyze cylinder pressure, manifold pressure and instantaneous crank speed signals measured from a 4 cylinder, 1.6 Litre, Gasoline Direct Injection Engine at different speed conditions to identify the frequency coupling between these signals. This work uses Ensemble Empirical Mode Decomposition (EEMD) as a de-noising method and Bispectral analysis for examining the presence of a frequency coupling from the signals. This paper will demonstrate a systematic approach followed for employing EEMD and Bispectral analysis in a GDI engine for deriving frequency coupling details and its significance.

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Section: Signal Processing Methodsmentioning

confidence: 99%

“…Bispectral analysis has found its application in various fields such as speech analysis [21], fault diagnostics of vibration data [20], wave analysis [22], underwater acoustics [18], sonar data [23], detecting forgery [24], musical [25], medical application [19] and many more. This signal processing method will be employed in the present work.…”

Section: /19/2016mentioning

confidence: 99%

Frequency Coupling Analysis in Spark Ignition Engine Using Bispectral Method and Ensemble Empirical Mode Decomposition

Yacoubi¹,

Samuel²

2022

SAE Technical Paper Series

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“…Bicoherence is mostly used in fault diagnosis because of its ability to trace and analyze multifrequency components. It is most effective in analyzing systems with nonlinear coupling between frequencies and is useful in detecting and quantifying the presence of nonlinearity, thus indicating the severity of the fault in the machine [48,49]. Bicoherence is also considered as a tool to analyze the coupling effects between states of a dynamical system at different frequencies [50][51][52].…”

Section: Bicoherence Bispectral Analysis or Bicoherence Is A Powerfumentioning

confidence: 99%

Chaotic Dynamics of an Airfoil with Higher‐Order Plunge and Pitch Stiffnesses in Incompressible Flow

et al. 2019

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Dynamical properties of a two-dimensional airfoil model with higher-order strong nonlinearities are investigated. Firstly, a state-space model is derived considering the plunge and pitch stiffnesses as generalized functions. Then, a stiffness function having square, cubic, and fifth-power nonlinearities is considered for both plunging and pitching stiffnesses, and the dimensionless state equations are derived. Various dynamical properties of the proposed model are investigated using equilibrium points, eigenvalues, and Lyapunov exponents. To further analyze the dynamical behavior of the system, bifurcation plots are derived. It is interesting to note that the new airfoil model with higher-order nonlinearities shows multistability with changing airspeed, and there are infinitely countable number of coexisting attractors generally called as megastability. Both multistability and megastability features of the airfoil model were not captured earlier in the literatures. To be clear, it is the first time a megastable feature is exposed in a physical system. Finally, to analyze the multifrequency effects of the airfoil model, we have presented the bicoherence plots.

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Application of Bicoherence Analysis on Vibration Data for Condition Based Monitoring of Rotating Machinery

Halim

Shah

Choudhury

et al. 2008

IFAC Proceedings Volumes

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Fault Detection of Rotating Machinery From Bicoherence Analysis of Vibration Data

Cited by 4 publications

References 4 publications

Frequency Coupling Analysis in Spark Ignition Engine Using Bispectral Method and Ensemble Empirical Mode Decomposition

Frequency Coupling Analysis in Spark Ignition Engine Using Bispectral Method and Ensemble Empirical Mode Decomposition

Chaotic Dynamics of an Airfoil with Higher‐Order Plunge and Pitch Stiffnesses in Incompressible Flow

Application of Bicoherence Analysis on Vibration Data for Condition Based Monitoring of Rotating Machinery

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